Venous leg ulcers account for 40 to 70% of all chronic wounds, afflict 1 million Americans per year, and standard treatment for these patients is estimated to cost more than l billion dollars per year. The current standard therapy for these wounds is a limb compression bandage, which at best has a success rate of 70 to 80%. Very little information exists that can be used to predict who will have a successful outcome. The hypothesis of this proposal is that there are identifiable risk factors that can be used to predict which individuals will have a successful outcome. A statistically powerful prediction model will be created using logistic regression analysis based on a dataset derived from the candidate's clinical practice and the control inns of industry sponsored trials. This model will be validated using a split sample technique, and by a prospective study in Penn's Cutaneous Ulcer Center. It will provide information that will guide the design of studies to evaluate new therapies, establish relationships between risk factor and wound healing which will lead to properly controlled hypothesis driven research, and may demonstrate two clinically distinct subsets of patients with venous led ulcers.